The present application describes computerized methods for processing data relating to transactions, data processing systems for data relating to transactions, a computer data structure for data relating to transactions, and computer program products for processing data relating to transactions.
Data mining refers in general to data-driven approaches for extracting hidden information from input data. The amount of input data may be huge, and therefore data mining techniques typically consider how to effectively process large amounts of data. Consider manufacturing of products as an example. There, the input data may include various pieces of data relating to origin and features of components. The aim of data mining in the context of manufacturing may be to resolve problems relating to quality analysis and quality assurance. Data mining may be used, for example, for root cause analysis, for early warning systems within the manufacture plant, and for reducing warranty claims. As a second example, consider various information technology systems. There, data mining may further be used for intrusion detection, system monitoring, and problem analyses. Data mining has also various other uses, for example, in retail and services, where typical customer behavior can be analyzed, and in medicine and life sciences for finding causal relations in clinical studies.